{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\research\works\주제55_빈집_투표\data\code.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}30 Sep 2025, 16:15:09

{com}. import excel "C:\research\works\주제55_빈집_투표\data\df.xlsx", sheet("data") firstrow clear
{res}
{com}. gen ln_population_density = ln( population_density )

. 
. gen ln_economy = ln( average_premium )

. 
. encode district, gen(district_1)

. 
. encode metropolisandprovince , gen(province_1)

. 
. gen ln_vote_margin = ln( vote_margin )

. 
. xtset district_1 year
{res}{txt}{col 8}panel variable:  {res}district_1 (strongly balanced)
{txt}{col 9}time variable:  {res}{col 25}year, 2016 to 2022, but with gaps
{txt}{col 17}delta:  {res}1 unit

{com}. 
. 
. 
. 
. 
. reg turn_out vacant_rate ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin capital_region honam_region youngnam_region gangwon_region chungcheong_region, vce (cluster district )

{txt}Linear regression                               Number of obs     = {res}     1,008
                                                {txt}F(16, 251)        =  {res}   736.82
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8881
                                                {txt}Root MSE          =    {res} .02843

{txt}{ralign 87:(Std. Err. adjusted for {res:252} clusters in district)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}             turn_out{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}vacant_rate {c |}{col 23}{res}{space 2}-.2294372{col 35}{space 2} .0583065{col 46}{space 1}   -3.94{col 55}{space 3}0.000{col 63}{space 4}-.3442695{col 76}{space 3}-.1146049
{txt}ln_population_density {c |}{col 23}{res}{space 2}-.0024248{col 35}{space 2} .0015534{col 46}{space 1}   -1.56{col 55}{space 3}0.120{col 63}{space 4}-.0054842{col 76}{space 3} .0006347
{txt}{space 11}ln_economy {c |}{col 23}{res}{space 2} .0617778{col 35}{space 2} .0135291{col 46}{space 1}    4.57{col 55}{space 3}0.000{col 63}{space 4} .0351327{col 76}{space 3} .0884229
{txt}{space 16}palma {c |}{col 23}{res}{space 2}  .003119{col 35}{space 2} .0022884{col 46}{space 1}    1.36{col 55}{space 3}0.174{col 63}{space 4}-.0013879{col 76}{space 3}  .007626
{txt}{space 13}high_edu {c |}{col 23}{res}{space 2} .0682285{col 35}{space 2} .0253612{col 46}{space 1}    2.69{col 55}{space 3}0.008{col 63}{space 4} .0182805{col 76}{space 3} .1181764
{txt}{space 8}homeownership {c |}{col 23}{res}{space 2} .0070556{col 35}{space 2} .0017744{col 46}{space 1}    3.98{col 55}{space 3}0.000{col 63}{space 4}  .003561{col 76}{space 3} .0105503
{txt}{space 13}mean_age {c |}{col 23}{res}{space 2} .0026527{col 35}{space 2} .0005082{col 46}{space 1}    5.22{col 55}{space 3}0.000{col 63}{space 4} .0016518{col 76}{space 3} .0036535
{txt}{space 12}sex_ratio {c |}{col 23}{res}{space 2} .0006583{col 35}{space 2} .0000331{col 46}{space 1}   19.91{col 55}{space 3}0.000{col 63}{space 4} .0005931{col 76}{space 3} .0007234
{txt}{space 9}urbanization {c |}{col 23}{res}{space 2}-.0002411{col 35}{space 2} .0001599{col 46}{space 1}   -1.51{col 55}{space 3}0.133{col 63}{space 4}-.0005561{col 76}{space 3} .0000739
{txt}{space 9}presidential {c |}{col 23}{res}{space 2} .1037633{col 35}{space 2} .0020132{col 46}{space 1}   51.54{col 55}{space 3}0.000{col 63}{space 4} .0997984{col 76}{space 3} .1077282
{txt}{space 7}ln_vote_margin {c |}{col 23}{res}{space 2} .0013755{col 35}{space 2} .0009654{col 46}{space 1}    1.42{col 55}{space 3}0.155{col 63}{space 4}-.0005259{col 76}{space 3} .0032769
{txt}{space 7}capital_region {c |}{col 23}{res}{space 2}-.0518541{col 35}{space 2} .0065783{col 46}{space 1}   -7.88{col 55}{space 3}0.000{col 63}{space 4}-.0648098{col 76}{space 3}-.0388984
{txt}{space 9}honam_region {c |}{col 23}{res}{space 2}-.0114295{col 35}{space 2} .0058221{col 46}{space 1}   -1.96{col 55}{space 3}0.051{col 63}{space 4}-.0228959{col 76}{space 3} .0000369
{txt}{space 6}youngnam_region {c |}{col 23}{res}{space 2}-.0423199{col 35}{space 2} .0056284{col 46}{space 1}   -7.52{col 55}{space 3}0.000{col 63}{space 4}-.0534048{col 76}{space 3} -.031235
{txt}{space 7}gangwon_region {c |}{col 23}{res}{space 2}-.0429244{col 35}{space 2}  .006069{col 46}{space 1}   -7.07{col 55}{space 3}0.000{col 63}{space 4}-.0548771{col 76}{space 3}-.0309717
{txt}{space 3}chungcheong_region {c |}{col 23}{res}{space 2}-.0607447{col 35}{space 2} .0063896{col 46}{space 1}   -9.51{col 55}{space 3}0.000{col 63}{space 4}-.0733288{col 76}{space 3}-.0481605
{txt}{space 16}_cons {c |}{col 23}{res}{space 2}-.1863424{col 35}{space 2} .1459243{col 46}{space 1}   -1.28{col 55}{space 3}0.203{col 63}{space 4}-.4737345{col 76}{space 3} .1010496
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{com}. 
. 
. 
. 
. 
. fracreg probit turn_out vacant_rate ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin capital_region honam_region youngnam_region gangwon_region chungcheong_region, vce (cluster district )

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-614.41659}  
Iteration 1:{space 3}log pseudolikelihood = {res:-599.75177}  
Iteration 2:{space 3}log pseudolikelihood = {res: -599.7414}  
Iteration 3:{space 3}log pseudolikelihood = {res: -599.7414}  
{res}
{txt}Fractional probit regression{col 49}Number of obs{col 67}= {res}     1,008
{txt}{col 49}Wald chi2({res}16{txt}){col 67}= {res}  13794.30
{txt}{col 49}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res} -599.7414{txt}{col 49}Pseudo R2{col 67}= {res}    0.0246

{txt}{ralign 87:(Std. Err. adjusted for {res:252} clusters in district)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}             turn_out{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      z{col 55}   P>|z|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}vacant_rate {c |}{col 23}{res}{space 2}-.6927413{col 35}{space 2} .1719672{col 46}{space 1}   -4.03{col 55}{space 3}0.000{col 63}{space 4}-1.029791{col 76}{space 3}-.3556918
{txt}ln_population_density {c |}{col 23}{res}{space 2}-.0077925{col 35}{space 2} .0044995{col 46}{space 1}   -1.73{col 55}{space 3}0.083{col 63}{space 4}-.0166114{col 76}{space 3} .0010264
{txt}{space 11}ln_economy {c |}{col 23}{res}{space 2}  .189253{col 35}{space 2} .0412535{col 46}{space 1}    4.59{col 55}{space 3}0.000{col 63}{space 4} .1083975{col 76}{space 3} .2701084
{txt}{space 16}palma {c |}{col 23}{res}{space 2} .0091587{col 35}{space 2} .0070424{col 46}{space 1}    1.30{col 55}{space 3}0.193{col 63}{space 4}-.0046442{col 76}{space 3} .0229616
{txt}{space 13}high_edu {c |}{col 23}{res}{space 2} .2026323{col 35}{space 2} .0754067{col 46}{space 1}    2.69{col 55}{space 3}0.007{col 63}{space 4} .0548379{col 76}{space 3} .3504267
{txt}{space 8}homeownership {c |}{col 23}{res}{space 2} .0194691{col 35}{space 2} .0052493{col 46}{space 1}    3.71{col 55}{space 3}0.000{col 63}{space 4} .0091807{col 76}{space 3} .0297574
{txt}{space 13}mean_age {c |}{col 23}{res}{space 2} .0081561{col 35}{space 2} .0015042{col 46}{space 1}    5.42{col 55}{space 3}0.000{col 63}{space 4} .0052078{col 76}{space 3} .0111043
{txt}{space 12}sex_ratio {c |}{col 23}{res}{space 2} .0016992{col 35}{space 2}  .000095{col 46}{space 1}   17.89{col 55}{space 3}0.000{col 63}{space 4}  .001513{col 76}{space 3} .0018854
{txt}{space 9}urbanization {c |}{col 23}{res}{space 2} -.000764{col 35}{space 2} .0004671{col 46}{space 1}   -1.64{col 55}{space 3}0.102{col 63}{space 4}-.0016795{col 76}{space 3} .0001514
{txt}{space 9}presidential {c |}{col 23}{res}{space 2} .3109119{col 35}{space 2} .0059119{col 46}{space 1}   52.59{col 55}{space 3}0.000{col 63}{space 4} .2993248{col 76}{space 3} .3224989
{txt}{space 7}ln_vote_margin {c |}{col 23}{res}{space 2} .0045554{col 35}{space 2} .0027491{col 46}{space 1}    1.66{col 55}{space 3}0.098{col 63}{space 4}-.0008327{col 76}{space 3} .0099434
{txt}{space 7}capital_region {c |}{col 23}{res}{space 2}-.1544663{col 35}{space 2} .0191478{col 46}{space 1}   -8.07{col 55}{space 3}0.000{col 63}{space 4}-.1919952{col 76}{space 3}-.1169374
{txt}{space 9}honam_region {c |}{col 23}{res}{space 2}-.0329168{col 35}{space 2} .0170778{col 46}{space 1}   -1.93{col 55}{space 3}0.054{col 63}{space 4}-.0663887{col 76}{space 3} .0005551
{txt}{space 6}youngnam_region {c |}{col 23}{res}{space 2} -.126865{col 35}{space 2} .0163633{col 46}{space 1}   -7.75{col 55}{space 3}0.000{col 63}{space 4}-.1589365{col 76}{space 3}-.0947936
{txt}{space 7}gangwon_region {c |}{col 23}{res}{space 2}-.1293287{col 35}{space 2}  .017693{col 46}{space 1}   -7.31{col 55}{space 3}0.000{col 63}{space 4}-.1640062{col 76}{space 3}-.0946511
{txt}{space 3}chungcheong_region {c |}{col 23}{res}{space 2}-.1805364{col 35}{space 2} .0184408{col 46}{space 1}   -9.79{col 55}{space 3}0.000{col 63}{space 4}-.2166797{col 76}{space 3}-.1443931
{txt}{space 16}_cons {c |}{col 23}{res}{space 2}-2.146592{col 35}{space 2} .4466196{col 46}{space 1}   -4.81{col 55}{space 3}0.000{col 63}{space 4} -3.02195{col 76}{space 3}-1.271233
{txt}{hline 22}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. 
. 
. xtreg turn_out vacant_rate ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin capital_region honam_region youngnam_region gangwon_region chungcheong_region , re vce (cluster district )
{res}
{txt}Random-effects GLS regression                   Number of obs     = {res}     1,008
{txt}Group variable: {res}district_1                      {txt}Number of groups  = {res}       252

{txt}R-sq:                                           Obs per group:
     within  = {res}0.9429                                         {txt}min = {res}         4
{txt}     between = {res}0.5633                                         {txt}avg = {res}       4.0
{txt}     overall = {res}0.8863                                         {txt}max = {res}         4

                                                {txt}Wald chi2({res}16{txt})     =  {res} 16147.15
{txt}corr(u_i, X)   = {res}0{txt} (assumed)                    Prob > chi2       =     {res}0.0000

{txt}{ralign 87:(Std. Err. adjusted for {res:252} clusters in district)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}             turn_out{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      z{col 55}   P>|z|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}vacant_rate {c |}{col 23}{res}{space 2}-.2226296{col 35}{space 2} .0503812{col 46}{space 1}   -4.42{col 55}{space 3}0.000{col 63}{space 4}-.3213749{col 76}{space 3}-.1238842
{txt}ln_population_density {c |}{col 23}{res}{space 2}-.0019195{col 35}{space 2} .0014983{col 46}{space 1}   -1.28{col 55}{space 3}0.200{col 63}{space 4}-.0048561{col 76}{space 3} .0010171
{txt}{space 11}ln_economy {c |}{col 23}{res}{space 2} .0341382{col 35}{space 2} .0099176{col 46}{space 1}    3.44{col 55}{space 3}0.001{col 63}{space 4}    .0147{col 76}{space 3} .0535764
{txt}{space 16}palma {c |}{col 23}{res}{space 2} .0064282{col 35}{space 2} .0021819{col 46}{space 1}    2.95{col 55}{space 3}0.003{col 63}{space 4} .0021517{col 76}{space 3} .0107046
{txt}{space 13}high_edu {c |}{col 23}{res}{space 2} .0413566{col 35}{space 2} .0211152{col 46}{space 1}    1.96{col 55}{space 3}0.050{col 63}{space 4}-.0000284{col 76}{space 3} .0827417
{txt}{space 8}homeownership {c |}{col 23}{res}{space 2} .0049623{col 35}{space 2} .0014715{col 46}{space 1}    3.37{col 55}{space 3}0.001{col 63}{space 4} .0020783{col 76}{space 3} .0078464
{txt}{space 13}mean_age {c |}{col 23}{res}{space 2} .0027881{col 35}{space 2} .0004204{col 46}{space 1}    6.63{col 55}{space 3}0.000{col 63}{space 4} .0019641{col 76}{space 3} .0036121
{txt}{space 12}sex_ratio {c |}{col 23}{res}{space 2} .0007115{col 35}{space 2} .0000279{col 46}{space 1}   25.51{col 55}{space 3}0.000{col 63}{space 4} .0006569{col 76}{space 3} .0007662
{txt}{space 9}urbanization {c |}{col 23}{res}{space 2}-.0001853{col 35}{space 2} .0001163{col 46}{space 1}   -1.59{col 55}{space 3}0.111{col 63}{space 4}-.0004133{col 76}{space 3} .0000427
{txt}{space 9}presidential {c |}{col 23}{res}{space 2} .1008876{col 35}{space 2} .0017007{col 46}{space 1}   59.32{col 55}{space 3}0.000{col 63}{space 4} .0975544{col 76}{space 3} .1042209
{txt}{space 7}ln_vote_margin {c |}{col 23}{res}{space 2} .0029273{col 35}{space 2}  .000749{col 46}{space 1}    3.91{col 55}{space 3}0.000{col 63}{space 4} .0014593{col 76}{space 3} .0043952
{txt}{space 7}capital_region {c |}{col 23}{res}{space 2}-.0555798{col 35}{space 2}  .006227{col 46}{space 1}   -8.93{col 55}{space 3}0.000{col 63}{space 4}-.0677846{col 76}{space 3} -.043375
{txt}{space 9}honam_region {c |}{col 23}{res}{space 2}-.0154068{col 35}{space 2} .0057563{col 46}{space 1}   -2.68{col 55}{space 3}0.007{col 63}{space 4} -.026689{col 76}{space 3}-.0041246
{txt}{space 6}youngnam_region {c |}{col 23}{res}{space 2}-.0476064{col 35}{space 2} .0051246{col 46}{space 1}   -9.29{col 55}{space 3}0.000{col 63}{space 4}-.0576505{col 76}{space 3}-.0375623
{txt}{space 7}gangwon_region {c |}{col 23}{res}{space 2} -.047417{col 35}{space 2} .0053727{col 46}{space 1}   -8.83{col 55}{space 3}0.000{col 63}{space 4}-.0579473{col 76}{space 3}-.0368867
{txt}{space 3}chungcheong_region {c |}{col 23}{res}{space 2}-.0625766{col 35}{space 2} .0063622{col 46}{space 1}   -9.84{col 55}{space 3}0.000{col 63}{space 4}-.0750464{col 76}{space 3}-.0501069
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} .1108807{col 35}{space 2} .0991249{col 46}{space 1}    1.12{col 55}{space 3}0.263{col 63}{space 4}-.0834005{col 76}{space 3}  .305162
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              sigma_u {c |} {res} .01779735
              {txt}sigma_e {c |} {res} .02122361
                  {txt}rho {c |} {res} .41286609{txt}   (fraction of variance due to u_i)
{hline 22}{c BT}{hline 64}

{com}. 
. 
. 
. 
. 
. xtreg turn_out vacant_rate ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin, fe vce (cluster district )

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1008
{txt}Group variable: {res}district_1                      {txt}Number of groups   = {res}      252

{txt}R-sq:  within  = {res}0.9449                         {txt}Obs per group: min = {res}        4
{txt}       between = {res}0.1140                                        {txt}avg = {res}      4.0
{txt}       overall = {res}0.5414                                        {txt}max = {res}        4

                                                {txt}F({res}11{txt},{res}251{txt})          = {res}  1086.32
{txt}corr(u_i, Xb)  = {res}-0.6223                        {txt}Prob > F           =    {res}0.0000

{txt}{ralign 87:(Std. Err. adjusted for {res:252} clusters in district)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}             turn_out{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}vacant_rate {c |}{col 23}{res}{space 2}-.1750943{col 35}{space 2} .0675749{col 46}{space 1}   -2.59{col 55}{space 3}0.010{col 63}{space 4}-.3081804{col 76}{space 3}-.0420081
{txt}ln_population_density {c |}{col 23}{res}{space 2}-.0227606{col 35}{space 2} .0226573{col 46}{space 1}   -1.00{col 55}{space 3}0.316{col 63}{space 4}-.0673833{col 76}{space 3} .0218621
{txt}{space 11}ln_economy {c |}{col 23}{res}{space 2}-.0395479{col 35}{space 2}  .023602{col 46}{space 1}   -1.68{col 55}{space 3}0.095{col 63}{space 4} -.086031{col 76}{space 3} .0069353
{txt}{space 16}palma {c |}{col 23}{res}{space 2} .0123908{col 35}{space 2} .0031429{col 46}{space 1}    3.94{col 55}{space 3}0.000{col 63}{space 4} .0062009{col 76}{space 3} .0185807
{txt}{space 13}high_edu {c |}{col 23}{res}{space 2}-.0354036{col 35}{space 2} .0293798{col 46}{space 1}   -1.21{col 55}{space 3}0.229{col 63}{space 4}-.0932659{col 76}{space 3} .0224587
{txt}{space 8}homeownership {c |}{col 23}{res}{space 2} .0020553{col 35}{space 2}  .001561{col 46}{space 1}    1.32{col 55}{space 3}0.189{col 63}{space 4} -.001019{col 76}{space 3} .0051296
{txt}{space 13}mean_age {c |}{col 23}{res}{space 2} .0059111{col 35}{space 2} .0015249{col 46}{space 1}    3.88{col 55}{space 3}0.000{col 63}{space 4}  .002908{col 76}{space 3} .0089143
{txt}{space 12}sex_ratio {c |}{col 23}{res}{space 2} .0007694{col 35}{space 2} .0000291{col 46}{space 1}   26.44{col 55}{space 3}0.000{col 63}{space 4} .0007121{col 76}{space 3} .0008267
{txt}{space 9}urbanization {c |}{col 23}{res}{space 2} -.000116{col 35}{space 2} .0001391{col 46}{space 1}   -0.83{col 55}{space 3}0.405{col 63}{space 4}-.0003899{col 76}{space 3} .0001579
{txt}{space 9}presidential {c |}{col 23}{res}{space 2} .0973733{col 35}{space 2} .0017755{col 46}{space 1}   54.84{col 55}{space 3}0.000{col 63}{space 4} .0938766{col 76}{space 3}   .10087
{txt}{space 7}ln_vote_margin {c |}{col 23}{res}{space 2} .0033799{col 35}{space 2} .0008255{col 46}{space 1}    4.09{col 55}{space 3}0.000{col 63}{space 4} .0017542{col 76}{space 3} .0050056
{txt}{space 16}_cons {c |}{col 23}{res}{space 2} .9112316{col 35}{space 2}  .190996{col 46}{space 1}    4.77{col 55}{space 3}0.000{col 63}{space 4} .5350727{col 76}{space 3} 1.287391
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              sigma_u {c |} {res} .06922587
              {txt}sigma_e {c |} {res} .02122361
                  {txt}rho {c |} {res} .91408149{txt}   (fraction of variance due to u_i)
{hline 22}{c BT}{hline 64}

{com}. 
. 
. 
. 
. 
. xtreg turn_out vacant_rate ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin i.year, fe vce (cluster district )

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1008
{txt}Group variable: {res}district_1                      {txt}Number of groups   = {res}      252

{txt}R-sq:  within  = {res}0.9453                         {txt}Obs per group: min = {res}        4
{txt}       between = {res}0.1120                                        {txt}avg = {res}      4.0
{txt}       overall = {res}0.5744                                        {txt}max = {res}        4

                                                {txt}F({res}14{txt},{res}251{txt})          = {res}   828.95
{txt}corr(u_i, Xb)  = {res}-0.5798                        {txt}Prob > F           =    {res}0.0000

{txt}{ralign 87:(Std. Err. adjusted for {res:252} clusters in district)}
{hline 22}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 23}{c |}{col 35}    Robust
{col 1}             turn_out{col 23}{c |}      Coef.{col 35}   Std. Err.{col 47}      t{col 55}   P>|t|{col 63}     [95% Con{col 76}f. Interval]
{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}vacant_rate {c |}{col 23}{res}{space 2}-.1572989{col 35}{space 2} .0688095{col 46}{space 1}   -2.29{col 55}{space 3}0.023{col 63}{space 4}-.2928165{col 76}{space 3}-.0217813
{txt}ln_population_density {c |}{col 23}{res}{space 2}-.0172083{col 35}{space 2} .0224666{col 46}{space 1}   -0.77{col 55}{space 3}0.444{col 63}{space 4}-.0614554{col 76}{space 3} .0270387
{txt}{space 11}ln_economy {c |}{col 23}{res}{space 2}-.0991551{col 35}{space 2} .0504688{col 46}{space 1}   -1.96{col 55}{space 3}0.051{col 63}{space 4}-.1985513{col 76}{space 3} .0002412
{txt}{space 16}palma {c |}{col 23}{res}{space 2}  .013831{col 35}{space 2} .0034319{col 46}{space 1}    4.03{col 55}{space 3}0.000{col 63}{space 4} .0070721{col 76}{space 3} .0205899
{txt}{space 13}high_edu {c |}{col 23}{res}{space 2}-.0339935{col 35}{space 2} .0304005{col 46}{space 1}   -1.12{col 55}{space 3}0.265{col 63}{space 4} -.093866{col 76}{space 3}  .025879
{txt}{space 8}homeownership {c |}{col 23}{res}{space 2} .0019337{col 35}{space 2} .0016773{col 46}{space 1}    1.15{col 55}{space 3}0.250{col 63}{space 4}-.0013696{col 76}{space 3} .0052371
{txt}{space 13}mean_age {c |}{col 23}{res}{space 2} .0051586{col 35}{space 2} .0022657{col 46}{space 1}    2.28{col 55}{space 3}0.024{col 63}{space 4} .0006963{col 76}{space 3} .0096209
{txt}{space 12}sex_ratio {c |}{col 23}{res}{space 2} .0001914{col 35}{space 2} .0003878{col 46}{space 1}    0.49{col 55}{space 3}0.622{col 63}{space 4}-.0005723{col 76}{space 3}  .000955
{txt}{space 9}urbanization {c |}{col 23}{res}{space 2}-.0001019{col 35}{space 2} .0001423{col 46}{space 1}   -0.72{col 55}{space 3}0.474{col 63}{space 4}-.0003822{col 76}{space 3} .0001783
{txt}{space 9}presidential {c |}{col 23}{res}{space 2} .1636544{col 35}{space 2} .0391885{col 46}{space 1}    4.18{col 55}{space 3}0.000{col 63}{space 4} .0864742{col 76}{space 3} .2408345
{txt}{space 7}ln_vote_margin {c |}{col 23}{res}{space 2} .0031852{col 35}{space 2} .0008283{col 46}{space 1}    3.85{col 55}{space 3}0.000{col 63}{space 4} .0015539{col 76}{space 3} .0048165
{txt}{space 21} {c |}
{space 17}year {c |}
{space 16}2017  {c |}{col 23}{res}{space 2}-.0066428{col 35}{space 2} .0068372{col 46}{space 1}   -0.97{col 55}{space 3}0.332{col 63}{space 4}-.0201083{col 76}{space 3} .0068228
{txt}{space 16}2020  {c |}{col 23}{res}{space 2} .0692038{col 35}{space 2} .0384614{col 46}{space 1}    1.80{col 55}{space 3}0.073{col 63}{space 4}-.0065444{col 76}{space 3} .1449519
{txt}{space 16}2022  {c |}{col 23}{res}{space 2} .0059243{col 35}{space 2} .0141638{col 46}{space 1}    0.42{col 55}{space 3}0.676{col 63}{space 4}-.0219707{col 76}{space 3} .0338193
{txt}{space 21} {c |}
{space 16}_cons {c |}{col 23}{res}{space 2} 1.580896{col 35}{space 2} .6554647{col 46}{space 1}    2.41{col 55}{space 3}0.017{col 63}{space 4} .2899846{col 76}{space 3} 2.871808
{txt}{hline 22}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              sigma_u {c |} {res}  .0638143
              {txt}sigma_e {c |} {res} .02118754
                  {txt}rho {c |} {res} .90070907{txt}   (fraction of variance due to u_i)
{hline 22}{c BT}{hline 64}

{com}. 
. 
. 
. 
. 
. xtreg turn_out c.vacant_rate##c.vacancy_over_6months c.ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin i.year, fe vce (cluster metropolisandprovince )

{txt}Fixed-effects (within) regression               Number of obs      = {res}     1008
{txt}Group variable: {res}district_1                      {txt}Number of groups   = {res}      252

{txt}R-sq:  within  = {res}0.9469                         {txt}Obs per group: min = {res}        4
{txt}       between = {res}0.1740                                        {txt}avg = {res}      4.0
{txt}       overall = {res}0.6531                                        {txt}max = {res}        4

                                                {txt}F({res}16{txt},{res}17{txt})           = {res}  3029.08
{txt}corr(u_i, Xb)  = {res}-0.5120                        {txt}Prob > F           =    {res}0.0000

{txt}{ralign 102:(Std. Err. adjusted for {res:18} clusters in metropolisandprovince)}
{hline 37}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 38}{c |}{col 50}    Robust
{col 1}                            turn_out{col 38}{c |}      Coef.{col 50}   Std. Err.{col 62}      t{col 70}   P>|t|{col 78}     [95% Con{col 91}f. Interval]
{hline 37}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 25}vacant_rate {c |}{col 38}{res}{space 2} .1578333{col 50}{space 2} .1263587{col 61}{space 1}    1.25{col 70}{space 3}0.229{col 78}{space 4}-.1087604{col 91}{space 3} .4244269
{txt}{space 16}vacancy_over_6months {c |}{col 38}{res}{space 2} .0664173{col 50}{space 2} .0333134{col 61}{space 1}    1.99{col 70}{space 3}0.062{col 78}{space 4}-.0038679{col 91}{space 3} .1367025
{txt}{space 36} {c |}
c.vacant_rate#c.vacancy_over_6months {c |}{col 38}{res}{space 2}-.8582429{col 50}{space 2} .1992061{col 61}{space 1}   -4.31{col 70}{space 3}0.000{col 78}{space 4}-1.278531{col 91}{space 3}-.4379549
{txt}{space 36} {c |}
{space 15}ln_population_density {c |}{col 38}{res}{space 2}-.0164128{col 50}{space 2} .0251499{col 61}{space 1}   -0.65{col 70}{space 3}0.523{col 78}{space 4}-.0694744{col 91}{space 3} .0366488
{txt}{space 26}ln_economy {c |}{col 38}{res}{space 2}-.0316577{col 50}{space 2} .0795768{col 61}{space 1}   -0.40{col 70}{space 3}0.696{col 78}{space 4}  -.19955{col 91}{space 3} .1362346
{txt}{space 31}palma {c |}{col 38}{res}{space 2} .0121214{col 50}{space 2} .0058352{col 61}{space 1}    2.08{col 70}{space 3}0.053{col 78}{space 4}-.0001898{col 91}{space 3} .0244326
{txt}{space 28}high_edu {c |}{col 38}{res}{space 2}-.0299038{col 50}{space 2} .0216186{col 61}{space 1}   -1.38{col 70}{space 3}0.184{col 78}{space 4}-.0755149{col 91}{space 3} .0157074
{txt}{space 23}homeownership {c |}{col 38}{res}{space 2} .0036517{col 50}{space 2} .0030253{col 61}{space 1}    1.21{col 70}{space 3}0.244{col 78}{space 4}-.0027311{col 91}{space 3} .0100345
{txt}{space 28}mean_age {c |}{col 38}{res}{space 2} .0056809{col 50}{space 2} .0027333{col 61}{space 1}    2.08{col 70}{space 3}0.053{col 78}{space 4}-.0000858{col 91}{space 3} .0114477
{txt}{space 27}sex_ratio {c |}{col 38}{res}{space 2} .0000902{col 50}{space 2} .0007437{col 61}{space 1}    0.12{col 70}{space 3}0.905{col 78}{space 4}-.0014788{col 91}{space 3} .0016592
{txt}{space 24}urbanization {c |}{col 38}{res}{space 2}-.0000208{col 50}{space 2} .0001235{col 61}{space 1}   -0.17{col 70}{space 3}0.868{col 78}{space 4}-.0002813{col 91}{space 3} .0002397
{txt}{space 24}presidential {c |}{col 38}{res}{space 2} .1743818{col 50}{space 2}  .074374{col 61}{space 1}    2.34{col 70}{space 3}0.031{col 78}{space 4} .0174663{col 91}{space 3} .3312973
{txt}{space 22}ln_vote_margin {c |}{col 38}{res}{space 2} .0028383{col 50}{space 2} .0016126{col 61}{space 1}    1.76{col 70}{space 3}0.096{col 78}{space 4}-.0005641{col 91}{space 3} .0062407
{txt}{space 36} {c |}
{space 32}year {c |}
{space 31}2017  {c |}{col 38}{res}{space 2}-.0081685{col 50}{space 2} .0064425{col 61}{space 1}   -1.27{col 70}{space 3}0.222{col 78}{space 4} -.021761{col 91}{space 3} .0054241
{txt}{space 31}2020  {c |}{col 38}{res}{space 2} .0673395{col 50}{space 2} .0722324{col 61}{space 1}    0.93{col 70}{space 3}0.364{col 78}{space 4}-.0850575{col 91}{space 3} .2197365
{txt}{space 31}2022  {c |}{col 38}{res}{space 2}-.0101054{col 50}{space 2} .0149139{col 61}{space 1}   -0.68{col 70}{space 3}0.507{col 78}{space 4}-.0415709{col 91}{space 3} .0213601
{txt}{space 36} {c |}
{space 31}_cons {c |}{col 38}{res}{space 2} .7527035{col 50}{space 2} 1.001451{col 61}{space 1}    0.75{col 70}{space 3}0.463{col 78}{space 4}-1.360173{col 91}{space 3}  2.86558
{txt}{hline 37}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                             sigma_u {c |} {res}  .0540024
                             {txt}sigma_e {c |} {res} .02090847
                                 {txt}rho {c |} {res} .86963646{txt}   (fraction of variance due to u_i)
{hline 37}{c BT}{hline 64}

{com}. 
. 
. 
. mixed turn_out c.vacant_rate##c.vacancy_over_6months ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin i.year || province_1: vacancy_over_6months, variance || district_1: , vce(cluster province_1 )
{res}
{txt}Performing EM optimization: 
{res}
{txt}Performing gradient-based optimization: 
{res}
{txt}Iteration 0:{space 3}log pseudolikelihood = {res: 2290.7556}  
{res}{txt}Iteration 1:{space 3}log pseudolikelihood = {res: 2290.7558}  
{res}
{txt}Computing standard errors:
{res}
{txt}Mixed-effects regression{col 49}Number of obs{col 67}={col 69}{res}     1,008

{txt}{hline 16}{c TT}{hline 44}
{col 17}{c |}{col 23}No. of{col 36}Observations per Group
{col 2}Group Variable{col 17}{c |}{col 23}Groups{col 33}Minimum{col 44}Average{col 55}Maximum
{hline 16}{c +}{hline 44}
{res}{col 6}province_1{txt}{col 17}{c |}{res}{col 21}      18{col 31}        4{col 42}     56.0{col 53}      176
{col 6}district_1{txt}{col 17}{c |}{res}{col 21}     252{col 31}        4{col 42}      4.0{col 53}        4
{txt}{hline 16}{c BT}{hline 44}

{col 49}Wald chi2({res}16{txt}){col 67}={col 70}{res}182857.30
{txt}Log pseudolikelihood = {res} 2290.7558{col 49}{txt}Prob > chi2{col 67}={col 73}{res}0.0000

{txt}{ralign 102:(Std. Err. adjusted for {res:18} clusters in province_1)}
{hline 37}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 38}{c |}{col 50}    Robust
{col 1}                            turn_out{col 38}{c |}      Coef.{col 50}   Std. Err.{col 62}      z{col 70}   P>|z|{col 78}     [95% Con{col 91}f. Interval]
{hline 37}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 25}vacant_rate {c |}{col 38}{res}{space 2} .3148896{col 50}{space 2} .0962747{col 61}{space 1}    3.27{col 70}{space 3}0.001{col 78}{space 4} .1261946{col 91}{space 3} .5035846
{txt}{space 16}vacancy_over_6months {c |}{col 38}{res}{space 2} .1007925{col 50}{space 2} .0231779{col 61}{space 1}    4.35{col 70}{space 3}0.000{col 78}{space 4} .0553646{col 91}{space 3} .1462203
{txt}{space 36} {c |}
c.vacant_rate#c.vacancy_over_6months {c |}{col 38}{res}{space 2}-1.373149{col 50}{space 2} .2238657{col 61}{space 1}   -6.13{col 70}{space 3}0.000{col 78}{space 4}-1.811918{col 91}{space 3}-.9343804
{txt}{space 36} {c |}
{space 15}ln_population_density {c |}{col 38}{res}{space 2}-.0042404{col 50}{space 2} .0030807{col 61}{space 1}   -1.38{col 70}{space 3}0.169{col 78}{space 4}-.0102785{col 91}{space 3} .0017977
{txt}{space 26}ln_economy {c |}{col 38}{res}{space 2}  .077455{col 50}{space 2} .0400992{col 61}{space 1}    1.93{col 70}{space 3}0.053{col 78}{space 4}-.0011379{col 91}{space 3} .1560479
{txt}{space 31}palma {c |}{col 38}{res}{space 2} .0027418{col 50}{space 2} .0038371{col 61}{space 1}    0.71{col 70}{space 3}0.475{col 78}{space 4}-.0047787{col 91}{space 3} .0102624
{txt}{space 28}high_edu {c |}{col 38}{res}{space 2} .0348217{col 50}{space 2} .0342005{col 61}{space 1}    1.02{col 70}{space 3}0.309{col 78}{space 4}-.0322101{col 91}{space 3} .1018535
{txt}{space 23}homeownership {c |}{col 38}{res}{space 2} .0044591{col 50}{space 2} .0026544{col 61}{space 1}    1.68{col 70}{space 3}0.093{col 78}{space 4}-.0007434{col 91}{space 3} .0096617
{txt}{space 28}mean_age {c |}{col 38}{res}{space 2}  .003013{col 50}{space 2} .0013238{col 61}{space 1}    2.28{col 70}{space 3}0.023{col 78}{space 4} .0004185{col 91}{space 3} .0056076
{txt}{space 27}sex_ratio {c |}{col 38}{res}{space 2} .0000403{col 50}{space 2}  .000472{col 61}{space 1}    0.09{col 70}{space 3}0.932{col 78}{space 4}-.0008848{col 91}{space 3} .0009655
{txt}{space 24}urbanization {c |}{col 38}{res}{space 2}-.0001539{col 50}{space 2} .0001487{col 61}{space 1}   -1.03{col 70}{space 3}0.301{col 78}{space 4}-.0004453{col 91}{space 3} .0001375
{txt}{space 24}presidential {c |}{col 38}{res}{space 2} .1678975{col 50}{space 2} .0473952{col 61}{space 1}    3.54{col 70}{space 3}0.000{col 78}{space 4} .0750046{col 91}{space 3} .2607904
{txt}{space 22}ln_vote_margin {c |}{col 38}{res}{space 2} .0022524{col 50}{space 2} .0012958{col 61}{space 1}    1.74{col 70}{space 3}0.082{col 78}{space 4}-.0002872{col 91}{space 3} .0047921
{txt}{space 36} {c |}
{space 32}year {c |}
{space 31}2017  {c |}{col 38}{res}{space 2} .0020884{col 50}{space 2} .0070386{col 61}{space 1}    0.30{col 70}{space 3}0.767{col 78}{space 4}-.0117069{col 91}{space 3} .0158838
{txt}{space 31}2020  {c |}{col 38}{res}{space 2} .0594252{col 50}{space 2} .0527971{col 61}{space 1}    1.13{col 70}{space 3}0.260{col 78}{space 4}-.0440552{col 91}{space 3} .1629056
{txt}{space 31}2022  {c |}{col 38}{res}{space 2}-.0113194{col 50}{space 2}  .012699{col 61}{space 1}   -0.89{col 70}{space 3}0.373{col 78}{space 4} -.036209{col 91}{space 3} .0135703
{txt}{space 36} {c |}
{space 31}_cons {c |}{col 38}{res}{space 2}-.4500255{col 50}{space 2} .5036458{col 61}{space 1}   -0.89{col 70}{space 3}0.372{col 78}{space 4}-1.437153{col 91}{space 3}  .537102
{txt}{hline 37}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{hline 29}{c TT}{hline 48}
{col 30}{c |}{col 34}{col 46}Robust{col 63}
{col 3}Random-effects Parameters{col 30}{c |}{col 34}Estimate{col 45}Std. Err.{col 59}[95% Conf. Interval]
{hline 29}{c +}{hline 48}
{res}province_1{txt}: Independent{col 30}{c |}
{col 16}var(vacanc~s){col 30}{c |}{res}{col 33} .0010029{col 44} .0006878{col 58} .0002615{col 70} .0038459
{txt}{col 19}var(_cons){col 30}{c |}{res}{col 33} .0002076{col 44} .0001163{col 58} .0000693{col 70} .0006225
{txt}{hline 29}{c +}{hline 48}
{res}district_1{txt}: Identity{col 30}{c |}
{col 19}var(_cons){col 30}{c |}{res}{col 33} .0002732{col 44} .0000639{col 58} .0001728{col 70} .0004321
{txt}{hline 29}{c +}{hline 48}
{col 16}var(Residual){col 30}{c |}{res}{col 33} .0004324{col 44} .0000679{col 58} .0003179{col 70} .0005882
{txt}{hline 29}{c BT}{hline 48}

{com}. 
. 
. 
. interflex turn_out vacant_rate vacancy_over_6months ln_population_density ln_economy palma high_edu homeownership mean_age sex_ratio urbanization presidential ln_vote_margin, ylab(Turnout) dlab(Vacancy rate) xlab(Long-term vacancy rate) fe( province_1 year )
{res}Fixed effects included; clustered standard errors highly recommended
{txt}p value of Wald test: {res}0.1494

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\research\works\주제55_빈집_투표\data\code.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}30 Sep 2025, 16:16:10
{txt}{.-}
{smcl}
{txt}{sf}{ul off}